Astrocyte response to beta amyloid peptide 25-35

The following tutorial walks through the identification of biological themes associated with expression patterns using unsupervised clustering in a microarray dataset examining Alzheimer’s disease.

Before you begin, we recommend that you review the analysis summary. The top button of the four on the right will download it if you haven't already.

When you are ready to begin this hands-on tutorial, click the third button down on the right, labeled "Log in to the dataset with tutorial."

1. Select Projects in the menu bar on the left side of the screen labeled Control Panel. You will see “Projects” under the heading marked “Analysis.”

2. Click on the magnifying glass icon next to the “Astrocyte response to beta amyloid peptide 25-35 :: Filtered” project. This is a sub-project created from filtering the data within the “Astrocyte response to beta amyloid peptide 25-35” project. The initial analysis filtered the ~1,200 genes represented on the Affymetrix U34 Neuro GeneChip® based on the following parameters:
-applying ANOVA to the entire set
-applying a 5% false discovery rate (FDR)
-filtering for a minimum 1.5-fold change cutoff.
-quality = 1
The result of this filtering has provided a list of 173 genes that was saved as the sub-project and will be analyzed in this tutorial.

3. At the top of this page is a Project Summary of the project data, describing the Array and the Conditions. For this tutorial, there is one Group containing 5 time points.

4. Select Cluster from the list of analysis options.

5. Unsupervised clustering can be performed on the filtered data by using the PAM section, setting the "Clusters" in the PAM section to 2 from the pull-down menu, and using the defaults for the other settings. Click the "Search" button. A graph showing the center for each cluster will be displayed.

6. Each line graph depicts the gene expression pattern for that cluster. Overall, the clustering has a mean silhouette width of 0.550. The cluster with 114 genes contains genes that are upregulated at 12 hours. The cluster with 59 genes displays the opposite pattern, containing genes downregulated at 12 hours, and slowly increasing in expression over the next 4 days.

7. To view page-specific help documents for this or any page, select the question mark icon located at the upper right page corner. On this page, help documents are available for PAM and silhouettes (including the interpretation of the mean silhouette width).

8. To view the list of genes associated with a cluster, click on the graph. For this tutorial, select the graph for the cluster with 114 genes.

9. The resulting page shows the expression pattern of the 114 genes that were in the cluster. Recall that this is the heat map for the cluster of upregulated genes, peaking at the 12 hour time point. The heat map clearly displays this pattern.

10. To get an overview of the gene families that have been differentially regulated at this time point, click on the Ontology link to bring up the Ontology Report.

11. The Ontology Report lists the GO terms of genes in the previous gene list. Currently, they are displayed heirarchically. Click on Z-score Report to show only the significant terms.

12. Click on Molecular Function.

13. Since we began with a list of genes upregulated at 12 hours, the z-score report now lists the pathways that were affected at this time point. A positive z-score, like those involving ATP binding and kinase activity, indicate that those terms are significantly overrepresented. Negative z-scores indicate that a term is showing up less often than expected by chance.